Accuracy and feasibility of an android-based digital assessment tool for post stroke visual disorders - The StrokeVision App

Background: Visual impairment affects up to 70% of stroke survivors. We designed an app (StrokeVision) to facilitate screening for common post stroke visual issues (acuity, visual fields and visual inattention). We sought to describe the test-time, feasibility, acceptability and accuracy of our app based digital visual assessments against a) current methods used for bedside screening, and b) gold standard measures. Methods: Patients were prospectively recruited from acute stroke settings. Index tests were app based assessments of fields and inattention performed by a trained researcher. We compared against usual clinical screening practice of visual fields to confrontation including inattention assessment (simultaneous stimuli). We also compared app to gold standard assessments of formal kinetic perimetry (Goldman or Octopus Visual Field Assessment); and pencil and paper based tests of inattention (Albert’s, Star Cancellation, and Line Bisection). Results of inattention and field tests were adjudicated by a specialist Neuro-Ophthalmologist. All assessors were masked to each other’s results. Participants and assessors graded acceptability using a bespoke scale that ranged from 0 (completely unacceptable) to 10 (perfect acceptability). Results: Of 48 stroke survivors recruited, the complete battery of index and reference tests for fields was successfully completed in 45. Similar acceptability scores were observed for app-based (assessor median score 10 [IQR:9-10]; patient 9 [IQR:8-10]) and traditional bedside testing (assessor 10 [IQR:9-10; patient 10 [IQR:9-10]). Median test time was longer for app-based testing (combined time-to-completion of all digital tests 420 seconds [IQR:390-588]) when compared with conventional bedside testing (70 seconds, [IQR:40-70]) but shorter than gold standard testing (1260 seconds, [IQR:1005-1620]). Compared with gold standard assessments, usual screening practice demonstrated 79% sensitivity and 82% specificity for detection of a stroke-related field defect. This compares with 79% sensitivity and 88% specificity for StrokeVision digital assessment. Conclusion: StrokeVision shows promise as a screening tool for visual complications in the acute phase of stroke. The app is at least as good as usual screening and offers other functionality that may make it attractive for use in acute stroke